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Editorial Special issues on the 20th anniversary of the CMStatistics (Computational and Methodological Statistics) CMStatistics成立20周年编辑特刊（计算与方法论统计学）
IF 1.9
Econometrics and Statistics Pub Date : 2023-04-01 DOI: 10.1016/j.ecosta.2023.03.001
Ana Colubi (Co-Editor) , Erricos Kontoghiorghes (Editor-in-Chief)
{"title":"Editorial Special issues on the 20th anniversary of the CMStatistics (Computational and Methodological Statistics)","authors":"Ana Colubi (Co-Editor) , Erricos Kontoghiorghes (Editor-in-Chief)","doi":"10.1016/j.ecosta.2023.03.001","DOIUrl":"https://doi.org/10.1016/j.ecosta.2023.03.001","url":null,"abstract":"","PeriodicalId":54125,"journal":{"name":"Econometrics and Statistics","volume":"26 ","pages":"Pages 1-2"},"PeriodicalIF":1.9,"publicationDate":"2023-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50193194","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A New Statistic for Bayesian Hypothesis Testing 一种新的贝叶斯假设检验统计量
IF 1.9
Econometrics and Statistics Pub Date : 2023-04-01 DOI: 10.1016/j.ecosta.2021.10.009
Su Chen , Stephen G. Walker
{"title":"A New Statistic for Bayesian Hypothesis Testing","authors":"Su Chen ,&nbsp;Stephen G. Walker","doi":"10.1016/j.ecosta.2021.10.009","DOIUrl":"https://doi.org/10.1016/j.ecosta.2021.10.009","url":null,"abstract":"<div><p>A new Bayesian–inspired statistic<span><span> for hypothesis testing<span> is proposed which compares two posterior distributions; the observed posterior and the expected posterior under the </span></span>null<span> model. The Kullback–Leibler divergence between the two posterior distributions yields a test statistic which can be interpreted as a penalized log–Bayes factor with the penalty term converging to a constant as the sample size increases. Hence, asymptotically, the statistic behaves as a Bayes factor<span>. Viewed as a penalized Bayes factor, this approach solves the long standing issue of using improper priors with the Bayes factor, since only posterior summaries are needed for the new statistic. Further motivation for the new statistic is a minimal move from the Bayes factor which requires no tuning nor splitting of data into training and inference, and can use improper priors. Critical regions for the test can be assessed using frequentist notions of Type I error.</span></span></span></p></div>","PeriodicalId":54125,"journal":{"name":"Econometrics and Statistics","volume":"26 ","pages":"Pages 139-152"},"PeriodicalIF":1.9,"publicationDate":"2023-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50193294","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Dynamic Tobit models 动态Tobit模型
IF 1.9
Econometrics and Statistics Pub Date : 2023-04-01 DOI: 10.1016/j.ecosta.2021.08.012
Andew Harvey , Yin Liao
{"title":"Dynamic Tobit models","authors":"Andew Harvey ,&nbsp;Yin Liao","doi":"10.1016/j.ecosta.2021.08.012","DOIUrl":"https://doi.org/10.1016/j.ecosta.2021.08.012","url":null,"abstract":"<div><p><span><span>Score-driven models provide a solution to the problem of modeling time series<span> when the observations are subject to censoring and location and/or scale may change over time. The method applies to generalized t and EGB2 distributions, as well as to the normal distribution. </span></span>Explanatory variables<span> can be included, making static Tobit models a special case. A set of Monte Carlo experiments show that the score-driven model provides good forecasts even when the true model is parameter-driven. The viability of the new models is illustrated by fitting them to data on Chinese </span></span>stock returns.</p></div>","PeriodicalId":54125,"journal":{"name":"Econometrics and Statistics","volume":"26 ","pages":"Pages 72-83"},"PeriodicalIF":1.9,"publicationDate":"2023-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50193292","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Fast cluster bootstrap methods for linear regression models 线性回归模型的快速聚类自举方法
IF 1.9
Econometrics and Statistics Pub Date : 2023-04-01 DOI: 10.1016/j.ecosta.2021.11.009
James G. MacKinnon
{"title":"Fast cluster bootstrap methods for linear regression models","authors":"James G. MacKinnon","doi":"10.1016/j.ecosta.2021.11.009","DOIUrl":"https://doi.org/10.1016/j.ecosta.2021.11.009","url":null,"abstract":"<div><p>Efficient computational algorithms for bootstrapping linear regression models with clustered data<span><span> are discussed. For ordinary least squares (OLS) regression, a new algorithm is provided for the pairs cluster bootstrap, along with two algorithms for the wild cluster bootstrap. One of these is a new way to express an existing method. For instrumental variables (IV) regression, an efficient algorithm is provided for the wild restricted efficient cluster (WREC) bootstrap. All computations are based on matrices and vectors that contain </span>sums of squares<span> and cross-products for the observations within each cluster, which have to be computed just once before the bootstrap loop begins. Monte Carlo experiments are used to study the finite-sample properties of bootstrap Wald tests for OLS regression and of WREC bootstrap tests for IV regression.</span></span></p></div>","PeriodicalId":54125,"journal":{"name":"Econometrics and Statistics","volume":"26 ","pages":"Pages 52-71"},"PeriodicalIF":1.9,"publicationDate":"2023-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50193246","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 9
Arbitrage pricing theory, the stochastic discount factor and estimation of risk premia from portfolios 套利定价理论、随机贴现因子与投资组合风险溢价估计
IF 1.9
Econometrics and Statistics Pub Date : 2023-04-01 DOI: 10.1016/j.ecosta.2021.11.005
M. Hashem Pesaran , Ron P. Smith
{"title":"Arbitrage pricing theory, the stochastic discount factor and estimation of risk premia from portfolios","authors":"M. Hashem Pesaran ,&nbsp;Ron P. Smith","doi":"10.1016/j.ecosta.2021.11.005","DOIUrl":"https://doi.org/10.1016/j.ecosta.2021.11.005","url":null,"abstract":"<div><p>The arbitrage pricing theory (APT) attributes differences in expected returns to exposure to systematic risk factors. Two aspects of the APT are considered. Firstly, the factors in the statistical asset pricing model are related to a theoretically consistent set of factors defined by their conditional covariation with the stochastic discount factor (SDF) used to price securities within inter-temporal asset pricing models. It is shown that risk premia arise from non-zero correlation of observed factors with SDF and the pricing errors arise from the correlation of the errors in the statistical model with SDF. Secondly, the estimates of factor risk premia using portfolios are compared to those obtained using individual securities. It is shown that in the presence of pricing errors consistent estimation of risk premia requires a large number of not fully diversified portfolios. Also, in general, it is not possible to rank estimators using individual securities and portfolios in terms of their small sample bias.</p></div>","PeriodicalId":54125,"journal":{"name":"Econometrics and Statistics","volume":"26 ","pages":"Pages 17-30"},"PeriodicalIF":1.9,"publicationDate":"2023-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50193248","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Rage Against the Mean – A Review of Distributional Regression Approaches 对均值的愤怒——分布回归方法综述
IF 1.9
Econometrics and Statistics Pub Date : 2023-04-01 DOI: 10.1016/j.ecosta.2021.07.006
Thomas Kneib, Alexander Silbersdorff, Benjamin Säfken
{"title":"Rage Against the Mean – A Review of Distributional Regression Approaches","authors":"Thomas Kneib,&nbsp;Alexander Silbersdorff,&nbsp;Benjamin Säfken","doi":"10.1016/j.ecosta.2021.07.006","DOIUrl":"https://doi.org/10.1016/j.ecosta.2021.07.006","url":null,"abstract":"<div><p>Distributional regression models that overcome the traditional focus on relating the conditional mean of the response to explanatory variables and instead target either the complete conditional response distribution or more general features thereof have seen increasing interest in the past decade. The current state of distributional regression will be discussed, with a particular focus on the four most prominent model classes: (i) generalized additive models for location, scale and shape, (ii) conditional transformation models and distribution regression, (iii) density regression, and (iv) quantile and expectile regression. Characteristics of the different distributional regression approaches will be provided to establish a structured overview on the similarities and differences with respect to the required assumptions on the conditional response distribution, theoretical properties, and the availability of software implementations. In addition, challenges arising in the interpretability of distributional regression models will be discussed and all four approaches will be illustrated with an application analyzing determinants of income distributions from the German Socio-Economic Panel (GSOEP).</p></div>","PeriodicalId":54125,"journal":{"name":"Econometrics and Statistics","volume":"26 ","pages":"Pages 99-123"},"PeriodicalIF":1.9,"publicationDate":"2023-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.ecosta.2021.07.006","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50193296","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 44
Risk-return trade-off in international stock returns: Skewness and business cycles 国际股票收益的风险收益权衡:偏态与商业周期
Econometrics and Statistics Pub Date : 2023-03-01 DOI: 10.1016/j.ecosta.2023.02.004
Henri Nyberg, Christos Savva
{"title":"Risk-return trade-off in international stock returns: Skewness and business cycles","authors":"Henri Nyberg, Christos Savva","doi":"10.1016/j.ecosta.2023.02.004","DOIUrl":"https://doi.org/10.1016/j.ecosta.2023.02.004","url":null,"abstract":"The fundamental risk-return relation is examined with a flexible regime switching model combining the impact of skewness and business cycle regimes in stock returns. Key methodological and empirical findings point out the need for a highly nonlinear and non-Gaussian model to get a reliable picture on the risk-return relationship. With an international dataset of major countries to global financial markets, the empirical results show that accounting especially for skewness patterns leads to the expected positive risk-return relation, which is importantly also maintained over different business cycle conditions.","PeriodicalId":54125,"journal":{"name":"Econometrics and Statistics","volume":"262 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136051658","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
A Review of Outlier Detection and Robust Estimation Methods for High Dimensional Time Series Data 高维时间序列数据的离群值检测和鲁棒估计方法综述
IF 1.9
Econometrics and Statistics Pub Date : 2023-02-01 DOI: 10.1016/j.ecosta.2023.02.001
D. Peña, V. Yohai
{"title":"A Review of Outlier Detection and Robust Estimation Methods for High Dimensional Time Series Data","authors":"D. Peña, V. Yohai","doi":"10.1016/j.ecosta.2023.02.001","DOIUrl":"https://doi.org/10.1016/j.ecosta.2023.02.001","url":null,"abstract":"","PeriodicalId":54125,"journal":{"name":"Econometrics and Statistics","volume":"40 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2023-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73265197","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
A nonparametric spatial regression model using partitioning estimators 基于分区估计的非参数空间回归模型
IF 1.9
Econometrics and Statistics Pub Date : 2023-02-01 DOI: 10.1016/j.ecosta.2023.02.003
Jose Olmo, Marcos Sanso-Navarro
{"title":"A nonparametric spatial regression model using partitioning estimators","authors":"Jose Olmo, Marcos Sanso-Navarro","doi":"10.1016/j.ecosta.2023.02.003","DOIUrl":"https://doi.org/10.1016/j.ecosta.2023.02.003","url":null,"abstract":"","PeriodicalId":54125,"journal":{"name":"Econometrics and Statistics","volume":"18 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2023-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79414951","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A new test for common breaks in heterogeneous panel data models 异构面板数据模型中常见中断的新测试
IF 1.9
Econometrics and Statistics Pub Date : 2023-02-01 DOI: 10.1016/j.ecosta.2023.01.005
Peiyun Jiang, Eiji Kurozumi
{"title":"A new test for common breaks in heterogeneous panel data models","authors":"Peiyun Jiang, Eiji Kurozumi","doi":"10.1016/j.ecosta.2023.01.005","DOIUrl":"https://doi.org/10.1016/j.ecosta.2023.01.005","url":null,"abstract":"","PeriodicalId":54125,"journal":{"name":"Econometrics and Statistics","volume":"110 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2023-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76090848","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
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